Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis.

MLA

Dietrich, Stefan, et al. “Random Survival Forest in Practice: A Method for Modelling Complex Metabolomics Data in Time to Event Analysis.” International Journal of Epidemiology, vol. 45, no. 5, Oct. 2016, pp. 1406–20. EBSCOhost, https://doi.org/10.1093/ije/dyw145.

APA

Dietrich, S., Floegel, A., Troll, M., Kühn, T., Rathmann, W., Peters, A., Sookthai, D., von Bergen, M., Kaaks, R., Adamski, J., Prehn, C., Boeing, H., Schulze, M. B., Illig, T., Pischon, T., Knüppel, S., Wang-Sattler, R., & Drogan, D. (2016). Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis. International Journal of Epidemiology, 45(5), 1406–1420. https://doi.org/10.1093/ije/dyw145

Chicago

Dietrich, Stefan, Anna Floegel, Martina Troll, Tilman Kühn, Wolfgang Rathmann, Anette Peters, Disorn Sookthai, et al. 2016. “Random Survival Forest in Practice: A Method for Modelling Complex Metabolomics Data in Time to Event Analysis.” International Journal of Epidemiology 45 (5): 1406–20. doi:10.1093/ije/dyw145.